Latest
Dokki Blog
Practical guides to MCP servers, agentic research, AI workflows, and human–agent collaboration for teams building with AI.
Agentic Research & GTM: From Evidence to Execution
The short answer Agentic research and go-to-market work use AI agents to accelerate evidence collection, synthesis, and coordinated execution while people retain responsibility for consequential claim
MCP Fundamentals: Servers, Security, and Workflows
The short answer Model Context Protocol (MCP) is a standard way for an AI application to connect to external data and actions through a host, one or more clients, and specialized servers. Start with t
Best AI Visibility Tools for B2B Teams
The best AI visibility tool is the one that preserves the evidence your team needs to make a decision. For some teams that means a large prompt-and-source dataset connected to SEO research. For others
How to Monitor AI Search Visibility
AI search visibility is the observable record of how a brand, product, page, or source appears in AI-generated answers for a defined set of prompts. Monitoring it means repeating controlled prompt run
SEO Audit Template for Human + AI Teams
An SEO audit template is a repeatable record for turning search evidence into a prioritized, owned, and verifiable change queue. It should not end with a generic score. A useful audit tells a team wha
AI Agent Workflow: Research, Review, Handoff, and Reusable Context
An AI agent workflow is a repeatable sequence of states that lets an agent gather context, create a bounded change, hand work to another actor, obtain approval, execute an action, and verify the resul
What Is an AI Workspace? Architecture, Context, Permissions, and Human–Agent Collaboration
An AI workspace is a shared operating environment where people and AI agents can use the same governed context, work on the same durable artifacts, and move tasks through explicit review and approval
Product Roadmap Template with Evidence and Decision Gates
A product roadmap template should explain why an initiative deserves capacity, what evidence supports it, which decision gate it has passed, and what outcome would justify continuing. A timeline alone
PRD Template for AI-Native Product Teams
A PRD template for AI-native product teams must do more than describe a feature. It should preserve the evidence behind the problem, turn product intent into testable requirements, define what people
Knowledge Base Template for People and AI Agents
A knowledge base template for people and AI agents must make trust machine-readable. A folder tree helps humans browse, but reliable retrieval also needs source identity, ownership, permissions, verif
Notion vs Coda for AI Workflows and Team Knowledge
Notion and Coda both combine documents, structured data, collaboration, and automation, but their product philosophies are different. Notion starts as a connected workspace for knowledge, projects, an
Notion vs Google Docs for Human-AI Collaboration
Notion and Google Docs can both support human-AI collaboration, but they optimize different units of work. Google Docs is the stronger default when a team needs a familiar document, fast real-time coa
Notion vs Confluence for AI Knowledge Work
Notion and Confluence can both serve as a team knowledge system, but they begin from different operating models. Notion combines flexible pages, databases, projects, teamspaces, and integrated AI. Con
Habit Tracker Template for Reviewable AI-Assisted Routines
A habit tracker template should help you learn which routines are working, under what conditions, and with what evidence. For AI-assisted routines, it must also separate observation from recommendatio
To-Do List Template That Preserves Context and Ownership
A to-do list template becomes useful when every item carries enough context to be understood, owned, prioritized, and verified. The goal is not a longer checklist. It is a reliable work queue where pe
Weekly Planner Template for Human-Agent Work
A weekly planner template should protect attention and make commitments visible. For human-agent work, it must also separate AI proposals from approved tasks, reserve capacity for review and exception
Project Management Template for Human-Agent Teams
A project management template for human-agent teams must do more than organize tasks. It needs to preserve why the project exists, separate proposals from approved work, define what an AI agent may ch
Content Calendar Template for an AI-Assisted Editorial Workflow
A content calendar template should control the whole editorial lifecycle, not just show publish dates. The practical version connects strategy, brief, source evidence, draft, review, distribution, per
Meeting Notes Template for Decisions, Owners, and Follow-Ups
A useful meeting notes template does more than capture a conversation. It makes decisions explicit, gives every action one owner, preserves unresolved questions, and creates a reliable starting point
Meeting Notes That Become Actions: A Practical AI Workflow
Meeting notes create value only when they preserve what was decided, turn commitments into owned work, and make follow-up visible. A transcript can capture every word and still leave the team unsure w
Notion Templates vs Agent Workspaces: What Reusable Work Needs
Notion templates are reusable starting structures for pages, databases, and recurring records. They are excellent when the work should begin the same way every time. They are not, by themselves, a com
Notion Custom Agents: Workflow Design, Permissions, and Cost
Notion Custom Agents can turn recurring knowledge work into a shared, background workflow. The difficult part is not creating an agent page. It is designing a bounded job that runs on the right events
What Are Notion Agents? Personal vs Custom Agents
Notion Agents are AI teammates inside Notion. The name covers two different operating models: the personal Notion Agent works on demand with the same permissions as the person using it, while Custom A
Notion MCP: Capabilities, Limits, and When to Use It
Notion MCP is Notion’s hosted Model Context Protocol server at https://mcp.notion.com/mcp . It lets compatible AI clients such as Claude Code, Cursor, VS Code, ChatGPT, and Codex search, fetch, create
Notion AI Credits Explained: How Custom Agent Costs Add Up
Notion credits are a usage budget for Custom Agents and other credit-based capabilities. Monthly Notion credits cost $10 per 1,000 credits, are shared across a workspace, reset monthly, and do not rol
Notion Pricing Explained: Plans, AI, and Real Team Cost
Notion’s public pricing currently lists Free at $0, Plus at $10 per member per month, Business at $20 per member per month, and Enterprise at custom pricing when the pricing page is set to yearly bill
Best Notion Alternatives for AI-Native Teams
Notion is a strong all-purpose workspace, but it is not the best operating model for every team. The right alternative depends less on which editor has the longest feature list and more on where work
What Is a Context Graph? A Practical Model for AI Workspaces
A context graph is a model of who and what exists in an organization, how those things relate, what happened between them over time, and which outcomes followed . It gives an AI system more than docum
Enterprise Knowledge Base: Architecture, Governance, and Ownership
An enterprise knowledge base is not simply a large collection of pages. It is an operating system for knowledge: a governed set of sources, records, owners, permissions, lifecycle rules, retrieval pat
AI Knowledge Management: From Retrieval to Reusable Work
AI knowledge management is the practice of making organizational knowledge findable, trustworthy, permission-aware, and reusable by both people and AI systems . It combines the discipline of knowledge
Best Knowledge Management Software for AI-Enabled Teams
Knowledge management software used to answer a storage question: where should the team put documents? AI-enabled teams need it to answer a harder operating question: which knowledge can people and age
Workplace Search vs Enterprise Search: What Teams Actually Need
Workplace search and enterprise search overlap, but they are not synonyms. Workplace search is an employee-facing experience for finding knowledge across the applications people use at work. Enterpris
Glean Pricing Explained: Licenses, AI Usage, and TCO
Glean does not publish a standard public per-user price list on its current website. Buyers are directed to request a demo and receive a commercial proposal. That means a trustworthy Glean pricing ana
Best Glean Alternatives for Enterprise Knowledge and AI Agents
The best Glean alternative depends on what you are actually replacing. Glean combines cross-application enterprise search, permissions-aware answers, a company knowledge graph, an AI assistant, and ag
AI Enterprise Search: How Grounded Answers Work Across Company Data
AI enterprise search is a permission-aware retrieval and answer system for company data. It connects to workplace sources, resolves the requesting user’s identity, retrieves only authorized evidence,
Best Enterprise Search Software: An Evaluation Framework
The best enterprise search software is not the product with the longest connector list or the most polished answer box. It is the system that can retrieve the right evidence for a specific user, prese
What Is Enterprise Search? Architecture, Permissions, and Use Cases
Enterprise search is a system for finding and answering questions across an organization’s authorized data sources. It combines connectors, indexing, relevance ranking, identity and access controls, a
What Is Agentic RAG? Architecture, Benefits, and Failure Modes
Agentic RAG is a retrieval-augmented generation architecture in which an agent actively controls retrieval instead of following one fixed search-and-answer pipeline. The agent can decide whether retri
AI Agent Orchestration: Architecture, State, and Human Control
AI agent orchestration is the control system that turns a goal into a bounded sequence of agent, model, retrieval, tool, and human steps. It decides what work should happen, which capability should pe
AI Agent Builder: What to Evaluate Before You Buy
An AI agent builder is not merely a prompt box with a publish button. It is the environment where a team defines an agent’s goal, knowledge, tools, identity, permissions, state, approvals, tests, depl
Enterprise Knowledge Graph: Entities, Permissions, and Provenance
An enterprise knowledge graph is a governed model of the important entities in a company, the relationships between them, and the evidence that supports those relationships. It connects people, teams,
Secure Enterprise Search: Permission-Aware Retrieval and Audit
Secure enterprise search means every result, snippet, citation, generated answer, cache entry, and diagnostic trace respects the requester’s current authority. It is not enough to protect the search A
Enterprise Search Architecture: Connectors, Indexes, ACLs, and Answers
Enterprise search architecture is the system behind a deceptively simple box. A user asks for a policy, customer decision, owner, incident, or precedent. The platform must discover evidence across man
Enterprise AI Assistant: Capabilities, Controls, and Evaluation
An enterprise AI assistant should do more than answer general questions in a chat box. It should find authorized company knowledge, show where claims came from, work across business systems, preserve
Hybrid Search Explained: Keyword, Vector, and Graph Retrieval
Hybrid search combines multiple retrieval methods so one weak signal does not decide what a user sees. Keyword search protects exact terms. Vector search finds semantic similarity. Graph retrieval fol
Context Engineering vs Prompt Engineering: What Changes in Production
Prompt engineering asks how to express an instruction so a model is more likely to follow it. Context engineering asks a larger question: what information, tools, state, permissions, and evidence shou
RAG Architecture for Enterprise Knowledge Systems
Retrieval-augmented generation looks simple in a demo: split documents, create embeddings, retrieve a few passages, and place them in a prompt. Enterprise RAG architecture is a different problem. The
What Is Fusion Editing? Humans and AI Agents in One Live Document
Fusion editing is a collaboration model in which people and AI agents read, write, comment, review, and hand work to one another inside the same live document. Instead of asking an AI for text in a se
Notion vs an Agent-Native Workspace: Which Is Better for AI Agents?
Notion is no longer just a human-authored wiki with an AI chat box. In 2026, it offers Notion Agent, Custom Agents, scheduled and triggered automation, page-level agent access, connected tools, MCP su
How to Run a Product Launch with AI Agents
AI agents can accelerate a product launch by researching the market, maintaining the launch plan, drafting channel assets, checking consistency, monitoring signals, and preparing post-launch analysis.
Agentic GTM Workflow: Research, Positioning, Content, and Review
An agentic GTM workflow uses specialized AI agents to research a market, structure evidence, propose positioning, produce coordinated assets, collect feedback, and update the plan under human review.
Best AI Tools for Research: A Workflow-First Comparison
The best AI research tool depends on the job. A product that is excellent at scanning the public web may be the wrong choice for a systematic literature review. A tool grounded in a fixed set of uploa
AI Market Research Workflow for Startups
AI can compress weeks of market research into days, but it cannot turn weak evidence into a reliable market decision. The strongest startup workflow combines AI-assisted discovery and synthesis with g
The AI Research Workflow: From Sources to a Reviewable Brief
An AI research workflow is a repeatable process that uses AI to accelerate discovery, extraction, comparison, and drafting while preserving source traceability and human review. The goal is not to gen
Linear MCP Workflow: Turn Research into Product Work
The short answer A Linear MCP workflow lets an AI agent find, create, and update Linear objects through a standardized tool interface. The valuable pattern is not “let the agent create tickets.” It is
HubSpot MCP Workflow for Agentic GTM Research
HubSpot MCP Workflow for Agentic GTM Research The short answer HubSpot’s remote MCP server gives compatible AI clients controlled access to CRM context through a hosted endpoint and OAuth. A high-valu
n8n and MCP: When Automation Needs a Shared Workspace
The short answer n8n and MCP solve different parts of an agentic workflow. n8n orchestrates triggers, APIs, branching, retries, and scheduled execution. MCP gives AI clients a standard way to discover
Playwright MCP Workflow: Research, Capture, and Publish
The Playwright MCP server gives MCP-compatible AI agents browser automation capabilities through structured page snapshots and browser tools. For research, its highest-value use is not autonomous brow
Connect Claude Code to a Shared Workspace with MCP
Claude Code can work with more than the files in your current repository. Through the Model Context Protocol (MCP), it can also search, read, and update a shared knowledge workspace. For teams, this c
Connect Codex to a Shared Knowledge Workspace with MCP
Codex is most effective when it can use both kinds of context a team depends on: the repository, files, terminal, and runtime evidence around the software; the shared product decisions, research, laun
MCP Security Checklist for Teams
MCP Security Checklist for Teams MCP server security requires more than connecting over OAuth or approving a server once. Teams must control which servers are trusted, which identity and scope each co
MCP Resources vs Tools vs Prompts: What Is the Difference?
Model Context Protocol servers can expose three core building blocks: resources , tools , and prompts . They solve different problems: Resources provide context. Tools perform actions. Prompts package
How to Build an MCP Server: A Practical Production Checklist
To build an MCP server, first define the smallest capability boundary, choose tools, resources, and prompts, implement them with an official SDK, connect a local stdio or remote Streamable HTTP transp
Local vs Remote MCP Servers: Which Should You Use?
Local vs Remote MCP Servers: Which Should You Use? Choose a local MCP server when the capability belongs to one machine, uses local files or developer tools, and should run under that user’s operating
MCP Server Architecture: Hosts, Clients, Servers, and Protocol Layers
MCP server architecture is a host–client–server system. A user-facing AI application acts as the host, creates one MCP client for each connected server, and coordinates the model and user experience.
What Is an MCP Server? Meaning, Architecture, and Examples
The short answer An MCP server is a program that exposes data, actions, or reusable prompts to AI applications through Model Context Protocol. It does not replace an API or an agent; it standardizes h
How to Summarize Research Papers with AI Without Losing the Sources
You can use AI to summarize a research paper safely when the summary remains attached to the paper’s identity, exact evidence, method, limitations, and publication status. Treat AI as an extraction an